Detecting Spatiotemporal Dynamic of Regional Electric Consumption Using NPP-VIIRS Nighttime Stable Light Data–A Case Study of Xi’an, China

Bin Guo,Dingming Zhang,Donghai Zhang,Yi Bian,Xiaoxia Wang,Yi Su

doi:10.1109/access.2020.3025013

Abstract

The available statistics on electric consumption (EC) can hardly show the spatial heterogeneity within political boundaries, and the previous studies paid few attention on the relations between EC and urban planning. The present study developed models between nighttime light values and EC using nighttime light images (NLI) from the Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) and statistical EC data from local government of Xi'an. A geographic information system (GIS) was utilized to map the distribution of EC on a grid scale, and the spatiotemporal dynamic of EC was obtained. In addition, a slope model and the EC grading threshold were conducted to determine the urban functional districts (UFD). The results were shown as follows: (1) the relation between TNL and EC is significant positive, and the performance of linear regression model (R 2 = 0.76, Root Mean Square Error (RMSE) = 9.44 × 10 4 , Mean Absolute Error (MAE) = 6.73 × 10 3 , Mean Percent Error (MPE) = -3.71%) is better than logarithmic model (R 2 = 0.68, RMSE = 1.09 × 10 5 , MAE = 7.77 × 10 4 , MPE = -5.44%). (2) In Xi'an, the EC continuously increased during 2013-2017, and the change of EC demonstrated obvious features that increased slowly in the city center, and spread outward to the surrounding region especially to the south of the study area. (3) The UFD have been divided into five sections including tourist district, commercial district, industrial zone, residential community, and ecological zone, respectively. This study will thus provide a reference and scientific basis for urban planning and rational allocation of electric power.

Highlights

Electricity is an important material basis of high living standards
(3) The urban functional districts (UFD) have been divided into five sections including tourist district, commercial district, industrial zone, residential community, and ecological zone, respectively
The total nighttime light (TNL) and electric consumption (EC) exhibited an obvious positive liner relation in Xi’an (R2 = 0.76, P < 0.05), and the result of validation illustrates the model was robust for simulating EC

Summary

Introduction

Electricity is an important material basis of high living standards. Urbanization and industrialization have led to a continuously increase in electric consumption. Carbon dioxide (CO2) generated by energy consumption, especially by electric consumption, is a major contributor to global warming. Urbanization is considered as one of the main drivers of global climate change [1]. Cities account for only 3% of the Earth’s land area, they account for 60-80% of global energy consumption and more than 70% of total greenhouse gas emissions [2], [3]. Urban areas account for 71% of global energy-related carbon emissions

Methods

Findings

Discussion

Conclusion